Methods for joint modelling of multiple longitudinal and survival outcomes

Lead Research Organisation: University of Cambridge

Abstract

When we want to predict the risk of a person developing a disease, or experiencing some other kind of medical event, we build a risk prediction model. The risk prediction model is used to inform someone about their future risk of disease and/or to make treatment decisions about the most appropriate way to manage their disease risk.
Usually a risk prediction model uses recent measurements of factors that are known to influence disease risk. We are exploring whether previous measurements of these risk factors, which are commonly stored in electronic medical records, can give additional information and help us to estimate the disease risk more precisely.
In this research programme we are exploring statistical methods which allow past measurements to be used in risk prediction, and developing statistical methods to determine whether a personalised screening schedule could help identify those at high disease risk.
One application of these methods is in cardiovascular risk prediction. This work will have important implications in the management of the risk of cardiovascular disease by improving the accuracy of cardiovascular risk prediction and developing a more individualised approach to the scheduling of cardiovascular risk assessments.
We will explore the potential of using data from electronic health records, such as records from GP practices, in this research. We anticipate this type of data will bring many challenges because the data were not originally collected for research purposes, and are considered “big data” because of the number of individuals involved.

Technical Summary

In many clinical applications we are interested in statistically modelling more than one outcome. These might be multiple longitudinal outcomes, such as the risk factors blood pressure, total cholesterol and high-density lipoprotein cholesterol for cardiovascular disease (CVD), or they may include a time-to-event, such as the first CVD event. The aim of this research programme is to develop and explore statistical methodology for the analysis of multiple outcomes. One area of focus will be dynamic risk prediction, where an individual’s prediction for the risk of an event occurring is updated in response to new measurements made of time-varying risk predictors. Methods for modelling repeated measurements of multiple risk predictors and a time-to-event outcome include joint modelling, where all outcomes are modelled simultaneously, and landmarking, where past repeated measurements are modelled separately from future times-to-events in a two-stage approach.

A clinical application which motivates this work is cardiovascular risk prediction. We are using data from electronic health records to develop a risk prediction tool for cardiovascular disease and to provide recommendations for the optimal scheduling of cardiovascular risk assessments. By projecting the risk of cardiovascular disease into the future we will aim to determine whether a person will likely be at high risk of cardiovascular disease in the future, and thereby to obtain a personalised recommendation for the time to schedule the next risk assessment. Using data from electronic health records for clinical research can be challenging because this data has not been collected for research purposes. We will explore the impact of informative observation of risk factor measurements because these measurements may have been taken in response to the state of health of the individual. There will also be computational challenges in the application of complex statistical methods to such big data. Additional questions we will explore in this context include the improvement in predictive accuracy that could be achieved by including other aspects of the risk factor trajectory in a prediction model, such as the slope of the longitudinal trajectory, or the variability in the repeated measurements, and the use of decision theory in obtaining the personalised recommendations. This work will have important implications in the management of the risk of cardiovascular disease.

Another application which motivates this programme of research is to understand the relationship between lung function and survival in cystic fibrosis. We are using joint modelling to assess whether the effect of sex on survival in cystic fibrosis patients is mediated by lung function, and will further explore the role of body mass index.

Publications

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Cassell A (2018) The epidemiology of multimorbidity in primary care: a retrospective cohort study. in The British journal of general practice : the journal of the Royal College of General Practitioners

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Marta GN (2019) Effectiveness of different accelerated partial breast irradiation techniques for the treatment of breast cancer patients: Systematic review using indirect comparisons of randomized clinical trials. in Reports of practical oncology and radiotherapy : journal of Greatpoland Cancer Center in Poznan and Polish Society of Radiation Oncology

 
Description Citation in paper on care planning for dementia patients
Geographic Reach Multiple continents/international 
Policy Influence Type Citation in clinical reviews
 
Description Lecturer on short course, An introduction to R statistical software.
Geographic Reach Local/Municipal/Regional 
Policy Influence Type Influenced training of practitioners or researchers
 
Description Blood pressure variability 
Organisation University of Bristol
Country United Kingdom 
Sector Academic/University 
PI Contribution Intellectual input, data analysis, writing
Collaborator Contribution Intellectual input
Impact One paper published in Statistics in Medicine
Start Year 2016
 
Description Blood pressure variability 
Organisation University of Mississippi
Department Department of Data Science
Country United States 
Sector Academic/University 
PI Contribution Intellectual input, data analysis, writing
Collaborator Contribution Intellectual input
Impact One paper published in Statistics in Medicine
Start Year 2016
 
Description Breast cancer systematic reviews 
Organisation Hospital Sirio Libanes, Sao Paulo
Country Brazil 
Sector Hospitals 
PI Contribution Intellectual input, writing and data analysis.
Collaborator Contribution Intellectual input, literature searches, data extraction and analyses.
Impact One Cochrane review has been published. A second Cochrane review is under review. A third paper has been published in Reports of Practical Oncology and Radiotherapy.
Start Year 2012
 
Description Breast cancer systematic reviews 
Organisation The Cochrane Collaboration
Department Brazilian Cochrane Centre (BCC)
Country Brazil 
Sector Charity/Non Profit 
PI Contribution Intellectual input, writing and data analysis.
Collaborator Contribution Intellectual input, literature searches, data extraction and analyses.
Impact One Cochrane review has been published. A second Cochrane review is under review. A third paper has been published in Reports of Practical Oncology and Radiotherapy.
Start Year 2012
 
Description Cardiovascular disease risk prediction using electronic health records 
Organisation Australian National University (ANU)
Department National Centre for Epidemiology and Population Health
Country Australia 
Sector Academic/University 
PI Contribution Intellectual input and statistical analysis
Collaborator Contribution Intellectual input and data provision
Impact One paper published by the American Journal of Epidemiology, one paper in preparation.
Start Year 2013
 
Description Cardiovascular disease risk prediction using electronic health records 
Organisation University College London
Department Department of Chemistry
Country United Kingdom 
Sector Academic/University 
PI Contribution Intellectual input and statistical analysis
Collaborator Contribution Intellectual input and data provision
Impact One paper published by the American Journal of Epidemiology, one paper in preparation.
Start Year 2013
 
Description Cystic fibrosis 
Organisation Lancaster University
Department Faculty of Health and Medicine
Country United Kingdom 
Sector Academic/University 
PI Contribution Intellectual input, data analysis, writing.
Collaborator Contribution Intellectual input, writing
Impact Article published in JRSSB, DOI 10.1111/rssb.12060. A second paper is ready for submission.
Start Year 2011
 
Description Cystic fibrosis 
Organisation Newcastle University
Department School of Mathematics and Statistics
Country United Kingdom 
Sector Academic/University 
PI Contribution Intellectual input, data analysis, writing.
Collaborator Contribution Intellectual input, writing
Impact Article published in JRSSB, DOI 10.1111/rssb.12060. A second paper is ready for submission.
Start Year 2011
 
Description Cystic fibrosis 
Organisation University of Liverpool
Department Institute of Psychology, Health and Society
Country United Kingdom 
Sector Academic/University 
PI Contribution Intellectual input, data analysis, writing.
Collaborator Contribution Intellectual input, writing
Impact Article published in JRSSB, DOI 10.1111/rssb.12060. A second paper is ready for submission.
Start Year 2011
 
Description Cystic fibrosis landmarking 
Organisation London School of Hygiene and Tropical Medicine (LSHTM)
Department Medical Statistics
Country United Kingdom 
Sector Academic/University 
PI Contribution Intellectual input and computing code
Collaborator Contribution Intellectual input, computing code and data analysis.
Impact One paper published in Epidemiology.
Start Year 2016
 
Description Prediction of post-surgery rupture of abdominal aortic anuerysms 
Organisation Imperial College London
Department Department of Surgery and Cancer
Country United Kingdom 
Sector Academic/University 
PI Contribution Intellectual input, data analysis
Collaborator Contribution Intellectual input, data provision
Impact One paper published as a Health Technology Assessment report, one paper published in the British Journal of Surgery.
Start Year 2015
 
Description Prediction of post-surgery rupture of abdominal aortic anuerysms 
Organisation University of Hamburg
Department Department of Vascular Medicine
PI Contribution Intellectual input, data analysis
Collaborator Contribution Intellectual input, data provision
Impact One paper published as a Health Technology Assessment report, one paper published in the British Journal of Surgery.
Start Year 2015
 
Description Prediction of post-surgery rupture of abdominal aortic anuerysms 
Organisation University of Helsinki
Country Finland 
Sector Academic/University 
PI Contribution Intellectual input, data analysis
Collaborator Contribution Intellectual input, data provision
Impact One paper published as a Health Technology Assessment report, one paper published in the British Journal of Surgery.
Start Year 2015
 
Description Prediction of post-surgery rupture of abdominal aortic anuerysms 
Organisation University of Leicester
Department Department of Health Sciences
Country United Kingdom 
Sector Academic/University 
PI Contribution Intellectual input, data analysis
Collaborator Contribution Intellectual input, data provision
Impact One paper published as a Health Technology Assessment report, one paper published in the British Journal of Surgery.
Start Year 2015
 
Description Splines for joint modelling 
Organisation Medical Research Council (MRC)
Country United Kingdom 
Sector Academic/University 
PI Contribution Intellectual input and writing computer code
Collaborator Contribution Intellectual input
Impact One paper published in Statistics in Medicine, and one paper published in Biometrics.
Start Year 2013
 
Description Splines for joint modelling 
Organisation University of California, Berkeley
Department Department of Integrative Biology
Country United States 
Sector Academic/University 
PI Contribution Intellectual input and writing computer code
Collaborator Contribution Intellectual input
Impact One paper published in Statistics in Medicine, and one paper published in Biometrics.
Start Year 2013
 
Description Press coverage for work on epidemiology of multimorbidity in primary care 
Form Of Engagement Activity A press release, press conference or response to a media enquiry/interview
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Media (as a channel to the public)
Results and Impact Kirsty Rhodes co-author on paper: 'The epidemiology of multimorbidity in primary care: a retrospective cohort study' which received wide-spread national media coverage, including articles in The Telegraph, Express, Sun, Daily Mail and GP Online. https://www.telegraph.co.uk/news/2018/03/13/one-four-adults-have-multiple-health-problems-startling-data/
Year(s) Of Engagement Activity 2018
URL http://bjgp.org/content/early/2018/03/12/bjgp18X695465